DBMS > Google BigQuery vs. Immudb vs. Interbase vs. Microsoft SQL Server vs. Splunk

System Properties Comparison Google BigQuery vs. Immudb vs. Interbase vs. Microsoft SQL Server vs. Splunk

Editorial information provided by DB-Engines

Name

Description

Large scale data warehouse service with append-only tables

An open source immutable (append-only) database with cryptographic verification which makes it tamper-resistant and fully auditable.

Light-weight proven RDBMS

originally from Borland

Microsofts flagship relational DBMS

Analytics Platform for Big Data

Primary database model

Secondary database models

Relational DBMS

Document store
Graph DBMS
Spatial DBMS

DB-Engines Ranking measures the popularity of database management systems
Trend Chart

Score	60.38
Rank	#19	Overall
	#13	Relational DBMS

Score	0.24
Rank	#305	Overall
	#43	Key-value stores

Score	4.61
Rank	#72	Overall
	#39	Relational DBMS

Score	824.29
Rank	#3	Overall
	#3	Relational DBMS

Score	86.45
Rank	#14	Overall
	#2	Search engines

Website

cloud.google.com/bigquery

github.com/codenotary/immudb
immudb.io

www.embarcadero.com/products/interbase

www.microsoft.com/en-us/sql-server

www.splunk.com

Technical documentation

cloud.google.com/bigquery/docs

docs.immudb.io

docs.embarcadero.com/products/interbase

learn.microsoft.com/en-US/sql/sql-server

docs.splunk.com/Documentation/Splunk

Developer

Google

Codenotary

Embarcadero

Microsoft

Splunk Inc.

Initial release

2010

2020

1984

1989

2003

Current release

1.2.3, April 2022

InterBase 2020, December 2019

SQL Server 2022, November 2022

License

Commercial or Open Source

commercial

Open Source

Apache Version 2.0

commercial

restricted free version is available

commercial

Limited free edition and free developer edition available

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

Implementation language

C++

Server operating systems

hosted

BSD
Linux
macOS
Solaris
Windows
z/OS

Android
iOS
Linux
OS X
Windows

Linux
Windows

Linux
OS X
Solaris
Windows

Data scheme

yes

schema-free

yes

Typing

predefined data types such as float or date

yes

XML support

Some form of processing data in XML format, e.g. support for XML data structures, and/or support for XPath, XQuery or XSLT.

export as XML data possible

yes

Secondary indexes

yes

SQL

Support of SQL

yes

SQL-like syntax

yes

Splunk Search Processing Language for search commands

APIs and other access methods

RESTful HTTP/JSON API

gRPC protocol
PostgreSQL wire protocol

ADO.NET
JDBC
ODBC

ADO.NET
JDBC
ODBC
OLE DB
Tabular Data Stream (TDS)

HTTP REST

Supported programming languages

.Net
Java
JavaScript
Objective-C
PHP
Python
Ruby

.Net
Go
Java
JavaScript (Node.js)
Python

.Net
C
C++
Delphi
Java
Object Pascal
PHP
Ruby

C#
C++
Delphi
Go
Java
JavaScript (Node.js)
PHP
Python
R
Ruby
Visual Basic

C#
Java
JavaScript
PHP
Python
Ruby

Server-side scripts

Stored procedures

user defined functions

in JavaScript

yes

Interbase procedure and trigger language

Transact SQL, .NET languages, R, Python and (with SQL Server 2019) Java

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

none

tables can be distributed across several files (horizontal partitioning); sharding through federation

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Interbase Change Views

yes, but depending on the SQL-Server Edition

Multi-source replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

Support to ensure data integrity after non-atomic manipulations of data

Since BigQuery is designed for querying data

ACID

A 'Transaction' in Splunk has a different meaning: grouping related events into a single one for later searching

Concurrency

Support for concurrent manipulation of data

yes

Multiversion concurreny control

yes

Durability

Support for making data persistent

yes

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

yes

User concepts

Access control

Access privileges (owner, writer, reader) on dataset, table or view level

Google Cloud Identity & Access Management (IAM)

fine grained access rights according to SQL-standard

Access rights for users and roles

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